10 citations · 15 across the 8 of their papers we have counts for
9 papers
Improving Music Source Separation with Diffusion and Consistency Refinement
Tornike Karchkhadze, Mohammad Rasool Izadi, Shuo Zhang +1
In this work, we propose an approach to music source separation that uses a generative diffusion model as a last-stage refinement on top of a deterministic separator, progressively…
Multi-Track MusicLDM: Towards Versatile Music Generation with Latent Diffusion Model
Tornike Karchkhadze, Mohammad Rasool Izadi, Ke Chen +2
Diffusion models have shown promising results in cross-modal generation tasks involving audio and music, such as text-to-sound and text-to-music generation. These text-controlled m…
Simultaneous Music Separation and Generation Using Multi-Track Latent Diffusion Models
Tornike Karchkhadze, Mohammad Rasool Izadi, Shlomo Dubnov
Diffusion models have recently shown strong potential in both music generation and music source separation tasks. Although in early stages, a trend is emerging towards integrating…
"It is okay to be uncommon": Quantizing Sound Event Detection Networks on Hardware Accelerators with Uncommon Sub-Byte Support
Yushu Wu, Xiao Quan, Mohammad Rasool Izadi +1
If our noise-canceling headphones can understand our audio environments, they can then inform us of important sound events, tune equalization based on the types of content we liste…
Latent CLAP Loss for Better Foley Sound Synthesis
Tornike Karchkhadze, Hassan Salami Kavaki, Mohammad Rasool Izadi +5
Foley sound generation, the art of creating audio for multimedia, has recently seen notable advancements through text-conditioned latent diffusion models. These systems use multimo…
HiSSNet: Sound Event Detection and Speaker Identification via Hierarchical Prototypical Networks for Low-Resource Headphones
N Shashaank, Berker Banar, Mohammad Rasool Izadi +3
Modern noise-cancelling headphones have significantly improved users' auditory experiences by removing unwanted background noise, but they can also block out sounds that matter to…
Affinity Mixup for Weakly Supervised Sound Event Detection
Mohammad Rasool Izadi, Robert Stevenson, Laura N. Kloepper
The weakly supervised sound event detection problem is the task of predicting the presence of sound events and their corresponding starting and ending points in a weakly labeled da…
Optimization of Graph Neural Networks with Natural Gradient Descent
Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson +1
In this work, we propose to employ information-geometric tools to optimize a graph neural network architecture such as the graph convolutional networks. More specifically, we devel…
Feature Level Fusion from Facial Attributes for Face Recognition
Mohammad Rasool Izadi
We introduce a deep convolutional neural networks (CNN) architecture to classify facial attributes and recognize face images simultaneously via a shared learning paradigm to improv…